Job Title:AI Data & Integration Engineer 

Location: Jersey ,NJ

Duration: 13 months 

Bill Rate: $78/hour (C2C)

Job Type: W-2, 1099, C2C

Client: To Be Discussed Later

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description:

Lead the design and delivery of secure, reliable and scalable data foundations and integrations for AI applications across a global law firm. This role enables AI assistants, enterprise search and agent workflows to use legal and business information with the appropriate context, permissions, quality and traceability.

 
KEY RESPONSIBILITIES:

• Data architecture: Own the architecture and technical design of data pipelines connecting document management, knowledge, client, matter and business systems to AI platforms. Establish reusable patterns for ingestion, transformation, indexing, access and synchronization.
• API integrations: Lead the design, implementation and operation of secure API integrations between enterprise systems, cloud services, AI platforms and agent tools. Define standards for authentication, authorization, versioning, error handling, observability, rate limiting and resilient data exchange.
• Permissions and governance: Ensure source permissions, information barriers and client restrictions remain effective throughout processing, integration and retrieval. Design mechanisms to propagate document updates, permission changes, retention decisions and deletions to downstream stores, indexes and consuming applications.
• Data models and products: Develop consistent data models linking clients, matters, people and documents. Provide governed data products, APIs and tool interfaces that enable AI applications and agents to retrieve and act on information safely.
• Evaluation partnership: Partner with AI evaluation engineers to turn data, retrieval and integration failure modes into measurable tests, regression suites and production controls, and use evaluation results to improve data and API design.
• Production troubleshooting: Diagnose complex production issues across source systems, APIs, data pipelines, indexes and consuming AI applications, balancing quality, security, performance, cost and maintainability.
• Technical leadership: Lead technical delivery across internal teams and external partners. Review architecture and code, mentor engineers, manage technical dependencies and translate business, legal and governance requirements into practical delivery plans.

 REQUIRED QUALIFICATIONS:

• Minimum five or more years in data engineering, integration engineering or a closely related discipline.
• Strong experience managing or leading teams that design, deliver and operate production application and data platforms and integrations.
• Deep practical experience designing and integrating RESTful and event-driven APIs, including authentication and authorization, API gateways, schema and contract management, versioning, retries, rate limits, error handling, observability and secure integration with enterprise and third-party systems.
• Strong conceptual understanding of large language models, including their capabilities, limitations and common failure modes, and how data quality, context, retrieval, permissions and integration design affect AI application performance and evaluation outcomes.
• Knowledge of unstructured document processing and retrieval-augmented generation (RAG), including search indexes, embeddings, hybrid retrieval, reranking and retrieval evaluation.
• Demonstrated ability to design secure data services and implement granular access controls and information barriers.
• Proficiency using coding agents to accelerate design, development, testing and troubleshooting, with sound judgement about human review and best practices for prompting, context management, validation, security and responsible use of generated code.
• Experience developing software in Python, Java or C#, applying sound engineering practices to reusable libraries, services and integration components.
• Experience with SDLC methodologies and associated development, automated testing and CI/CD tools such as Git, Jira and Jenkins.
• Experience making architectural decisions, leading complex technical delivery, reviewing designs and code, and developing other engineers.
• Ability to explain technical choices clearly to business, legal, security and governance stakeholders.
• Demonstrated ability to learn continuously in a rapidly evolving AI, data and integration landscape, critically assess new tools and techniques, and apply relevant advances pragmatically.

 PREFERRED QUALIFICATIONS:

• Legal or professional services industry experience.
• Familiarity with iManage or comparable document management systems.
• Experience with entity resolution, legal taxonomies and knowledge graphs.
• Experience with governed agent integrations such as Model Context Protocol (MCP).